Loop-based Markov Chain for Next Cell Prediction-Reference-Cited by-同舟云学术

Loop-based Markov Chain for Next Cell Prediction

Published:2023-02-28 Issue:2 Volume:5 Page:31-40
ISSN:2645-8969
Container-title:İstanbul Ticaret Üniversitesi Teknoloji ve Uygulamalı Bilimler Dergisi
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Author:

YALIN Bahadır¹^ORCID,YARKAN Serhan²^ORCID

Affiliation:

1. İSTANBUL TİCARET ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ

2. İSTANBUL TİCARET ÜNİVERSİTESİ

Abstract

With the development in the 5G, Software Defined Networking(SDN), Network Function Virtualization(NFV), which are the cornerstones of the 5G, are being developed as well. One of the biggest development of 5G is, dense of Machine-to-Machine (M2M) communication is excessively increased compared to older generations. Therefore, monitoring of these machines (or user equipment) will also become critical. Various Network Functions (NFs) have been given specific tasks so that this monitoring and other critical tasks can be done with the NFV innovation in 5G. Network Data Analytics Function (NWDAF), one of these functions, is responsible for creating analytics (i.e., statistics or predictions) by collecting data from other Network Functions. In particular, in order to generate predictions, it will be possible to use Machine Learning (ML) Models and Artificial Intelligence (AI) for the operations specified within the NWDAF. In this study, next possible cell for a User Equipment is predicted by using Markov Chain with novel loop-based approach.

Publisher

Istanbul Ticaret Universitesi

Reference14 articles.

1. 3GPP. (2018). TS 29.518. 3rd Generation Partnership Project.

2. 3rd Generation Partnership Project [3GPP]. (2019). TS 23.288. 3rd Generation Partnership Project.

3. Ben L., Chansu Y., Myungchul W., Seung-Min P., Weetit W., & Won-Tae K. (2011). Behavior-based mobility prediction for seamless handoffs in mobile wireless networks. Wireless Networks, 17(3), 645-658.

4. Bui N., Cesana M., Hosseini S. A., Liao Q., Malanchini I., & Widmer J. (2016, June 1). Anticipatory Networking in Future Generation Mobile Networks: a Survey , arXiv.

5. Changchun P., Ganke Y., Haichun L., & Junjie J. (2016). Predicting Human Mobility Based on Location Data Modeled by Markov Chains. 2016 Fourth International Conference on Ubiquitous Positioning, Indoor Navigation and Location Based Services (UPINLBS) (s. 145-151). Shanghai: IEEE.